Distributed foresighted energy management in smart-grid-powered cellular networks

This paper studies energy management in a smart grid-powered cellular network consisting of an independent system operator (ISO) and multiple geographically distributed aggregators. The aggregators have energy storage devices and can purchase energy from the electric grid via the ISO to serve their...

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Main Authors: Xinruo Zhang, Mohammad R. Nakhai, Gan Zheng, Sangarapillai Lambotharan, Jonathon Chambers
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Published: 2019
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Online Access:https://hdl.handle.net/2134/36952
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id rr-article-9565457
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spelling rr-article-95654572019-02-18T00:00:00Z Distributed foresighted energy management in smart-grid-powered cellular networks Xinruo Zhang (4950559) Mohammad R. Nakhai (7212815) Gan Zheng (2546086) Sangarapillai Lambotharan (1252278) Jonathon Chambers (7121624) Mechanical engineering not elsewhere classified untagged Mechanical Engineering not elsewhere classified This paper studies energy management in a smart grid-powered cellular network consisting of an independent system operator (ISO) and multiple geographically distributed aggregators. The aggregators have energy storage devices and can purchase energy from the electric grid via the ISO to serve their users. To account for the uncertainty of the renewable energy supply as well as the impacts of multiple aggregators on the electric grid and energy prices, a foresighted strategy combined with the adaptive ϵ -greedy method is developed for the aggregators to distributively and adaptively minimize the long-term overall cost of the system based on the ahead-of-time decision making of the storage pre-charging amount. Simulation results validate that the proposed strategy surpasses a recent learning-based storage management design and a myopic design. 2019-02-18T00:00:00Z Text Journal contribution 2134/36952 https://figshare.com/articles/journal_contribution/Distributed_foresighted_energy_management_in_smart-grid-powered_cellular_networks/9565457 CC BY 3.0
institution Loughborough University
collection Figshare
topic Mechanical engineering not elsewhere classified
untagged
Mechanical Engineering not elsewhere classified
spellingShingle Mechanical engineering not elsewhere classified
untagged
Mechanical Engineering not elsewhere classified
Xinruo Zhang
Mohammad R. Nakhai
Gan Zheng
Sangarapillai Lambotharan
Jonathon Chambers
Distributed foresighted energy management in smart-grid-powered cellular networks
description This paper studies energy management in a smart grid-powered cellular network consisting of an independent system operator (ISO) and multiple geographically distributed aggregators. The aggregators have energy storage devices and can purchase energy from the electric grid via the ISO to serve their users. To account for the uncertainty of the renewable energy supply as well as the impacts of multiple aggregators on the electric grid and energy prices, a foresighted strategy combined with the adaptive ϵ -greedy method is developed for the aggregators to distributively and adaptively minimize the long-term overall cost of the system based on the ahead-of-time decision making of the storage pre-charging amount. Simulation results validate that the proposed strategy surpasses a recent learning-based storage management design and a myopic design.
format Default
Article
author Xinruo Zhang
Mohammad R. Nakhai
Gan Zheng
Sangarapillai Lambotharan
Jonathon Chambers
author_facet Xinruo Zhang
Mohammad R. Nakhai
Gan Zheng
Sangarapillai Lambotharan
Jonathon Chambers
author_sort Xinruo Zhang (4950559)
title Distributed foresighted energy management in smart-grid-powered cellular networks
title_short Distributed foresighted energy management in smart-grid-powered cellular networks
title_full Distributed foresighted energy management in smart-grid-powered cellular networks
title_fullStr Distributed foresighted energy management in smart-grid-powered cellular networks
title_full_unstemmed Distributed foresighted energy management in smart-grid-powered cellular networks
title_sort distributed foresighted energy management in smart-grid-powered cellular networks
publishDate 2019
url https://hdl.handle.net/2134/36952
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